Analysis overview
This systematic review and meta-analysis evaluated the effects of NMDA receptor antagonists on locomotion in the social interaction test outcomes in animal models. Effect sizes were calculated as Hedges’ g and synthesized using multilevel random-effects models to account for dependency between multiple outcomes within experiments and studies.
Study landscape and evidence distribution
Alluvial plot
Distribution of species across NMDA receptor
antagonists.
Alluvial plot showing how effect sizes are distributed across animal
species and NMDA receptor antagonists.
Evidence maps
Evidence maps of experimental design
characteristics.
Bubble size represents the number of effect sizes (k), and color
indicates the mean Hedges’ g within each cell.
Main meta-analysis
Overall effect
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.180 1.086 51 no study_id
## sigma^2.2 0.201 0.449 117 no study_id/exp_id
##
## Test for Heterogeneity:
## Q(df = 169) = 992.023, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## 0.400 0.172 2.320 49.12 0.025 0.054 0.747 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t-test and confidence interval, df: Satterthwaite approx)Multilevel random-effects meta-analysis with robust variance estimation.
Orchard plot
Overall effect of NMDA receptor antagonists on locomotion in
the social interaction test.
Orchard plot summarizing study-level pooled effects with multilevel
heterogeneity.
Prediction interval for the overall effect
## estimate ci_lb ci_ub pi_lb pi_ub
## 1 0.4000693 0.05353985 0.7465987 -1.986984 2.787122Prediction interval for the overall effect. The 95% prediction interval reflects expected variability in the true effect size of a future study beyond sampling error.
## Component I.....
## 1 I2_Total 83.8
## 2 I2_study_id 71.6
## 3 I2_study_id/exp_id 12.2Multilevel heterogeneity estimates (I²).
Publication bias
Funnel plots
Funnel plot using standard error.
Funnel plot using inverse square root of total sample size.
Precision Effect Test (PET)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 2.719 1.649 51 no study_id
## sigma^2.2 0.164 0.405 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 168) = 939.914, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficient 2):¹
## F(df1 = 1, df2 = 9.95) = 15.750, p-val = 0.003
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## intrcpt -3.803 1.049 -3.626 18.78 0.002 -6.000 -1.606 **
## sqrt(vi) 7.717 1.945 3.969 9.95 0.003 3.381 12.053 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)PET (Precision Effect Test) model with robust variance estimation. The PET model evaluates small-study bias by regressing effect size on study precision.
Precision Effect Estimate with Standard Error (PEESE)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 2.255 1.502 51 no study_id
## sigma^2.2 0.139 0.373 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 168) = 937.527, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficient 2):¹
## F(df1 = 1, df2 = 6.74) = 9.524, p-val = 0.019
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## intrcpt -1.227 0.548 -2.237 33.54 0.032 -2.342 -0.112 *
## vi 5.265 1.706 3.086 6.74 0.019 1.200 9.331 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)PEESE (Precision Effect Estimate with Standard Error) model with robust variance estimation. The PEESE model provides an alternative bias-adjusted estimate using study variance.
Time-lag bias
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 0.976 0.988 51 no study_id
## sigma^2.2 0.213 0.462 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 168) = 911.561, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficient 2):¹
## F(df1 = 1, df2 = 25.73) = 7.738, p-val = 0.010
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## intrcpt 0.569 0.172 3.300 31.13 0.002 0.217 0.920 **
## year_c -0.052 0.019 -2.782 25.73 0.010 -0.090 -0.014 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)Time-lag meta-regression model. This model tests whether effect sizes change systematically over publication time. A significant slope would indicate temporal trends such as decline or inflation of reported effects.
Time-lag bias: effect size as a function of publication year.
Moderators
Moderator analyses were conducted using multilevel meta-analytic models with robust variance estimation to examine whether effect sizes differed across experimental and biological characteristics. Orchard plots display pooled effects for each moderator level, with study-level clustering and multilevel heterogeneity taken into account.
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.049 1.024 51 no study_id
## sigma^2.2 0.182 0.427 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 167) = 924.069, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficients 1:3):¹
## F(df1 = 3, df2 = 14.57) = 5.409, p-val = 0.010
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹
## nmda_antagonistKetamine -0.769 0.438 -1.756 6.05 0.129
## nmda_antagonistMK-801 0.552 0.276 2.004 23.17 0.057
## nmda_antagonistPhencyclidine 0.610 0.263 2.321 19.86 0.031
## ci.lb¹ ci.ub¹
## nmda_antagonistKetamine -1.839 0.301
## nmda_antagonistMK-801 -0.018 1.122 .
## nmda_antagonistPhencyclidine 0.061 1.158 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.245 1.116 51 no study_id
## sigma^2.2 0.201 0.448 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 167) = 989.781, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficients 1:3):¹
## F(df1 = 3, df2 = 3.14) = 1.151, p-val = 0.451
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## speciesMouse 0.548 0.350 1.566 6.99 0.161 -0.280 1.375
## speciesRat 0.356 0.200 1.783 40.23 0.082 -0.048 0.760
## speciesZebrafish 0.977 6.211 0.157 1 0.901 -77.943 79.897
##
## speciesMouse
## speciesRat .
## speciesZebrafish
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.098 1.048 51 no study_id
## sigma^2.2 0.199 0.446 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 167) = 952.857, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficients 1:3):¹
## F(df1 = 3, df2 = 22.47) = 6.504, p-val = 0.002
##
## Model Results:
##
## estimate se¹ tval¹
## developmental_stage_inductionAdult -0.093 0.327 -0.285
## developmental_stage_inductionJuvenile/Adolescent 0.666 0.215 3.099
## developmental_stage_inductionUnclear 0.762 0.224 3.401
## df¹ pval¹ ci.lb¹
## developmental_stage_inductionAdult 20.72 0.778 -0.773
## developmental_stage_inductionJuvenile/Adolescent 6.85 0.018 0.155
## developmental_stage_inductionUnclear 19.66 0.003 0.294
## ci.ub¹
## developmental_stage_inductionAdult 0.586
## developmental_stage_inductionJuvenile/Adolescent 1.176 *
## developmental_stage_inductionUnclear 1.230 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.246 1.116 51 no study_id
## sigma^2.2 0.209 0.458 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 165) = 975.166, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficients 1:5):¹
## F(df1 = 5, df2 = 0.8) = 0.178, p-val = 0.933
##
## Model Results:
##
## estimate se¹ tval¹ df¹
## nmda_administration_routeImmersion 0.977 6.231 0.157 1
## nmda_administration_routeIntraperitoneal 0.272 0.239 1.138 25.58
## nmda_administration_routeMinipump 0.731 0.756 0.967 1.4
## nmda_administration_routeSubcutaneous 0.522 0.280 1.867 20.3
## nmda_administration_routeUnclear -0.100 0.941 -0.107 1
## pval¹ ci.lb¹ ci.ub¹
## nmda_administration_routeImmersion 0.901 -78.201 80.155
## nmda_administration_routeIntraperitoneal 0.266 -0.219 0.763
## nmda_administration_routeMinipump 0.470 -4.281 5.743
## nmda_administration_routeSubcutaneous 0.076 -0.061 1.105 .
## nmda_administration_routeUnclear 0.932 -12.058 11.858
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
##
## Multivariate Meta-Analysis Model (k = 170; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.118 1.057 51 no study_id
## sigma^2.2 0.206 0.454 117 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 167) = 912.833, p-val < .001
##
## Number of estimates: 170
## Number of clusters: 51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
##
## Test of Moderators (coefficients 1:3):¹
## F(df1 = 3, df2 = 2.78) = 1.357, p-val = 0.412
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹
## nmda_scheduleAcute 0.199 0.153 1.297 21.49 0.208 -0.120
## nmda_scheduleContinuous 0.839 0.713 1.177 1.29 0.412 -4.555
## nmda_scheduleRepeated 0.648 0.256 2.535 14.23 0.024 0.101
## ci.ub¹
## nmda_scheduleAcute 0.518
## nmda_scheduleContinuous 6.233
## nmda_scheduleRepeated 1.196 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
Meta-regression
Cumulative exposure
##
## Multivariate Meta-Analysis Model (k = 166; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.183 1.088 49 no study_id
## sigma^2.2 0.218 0.466 115 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 164) = 947.249, p-val < .001
##
## Number of estimates: 166
## Number of clusters: 49
## Estimates per cluster: 0-12 (mean: 3.25, median: 2)
##
## Test of Moderators (coefficient 2):¹
## F(df1 = 1, df2 = 1.15) = 1.972, p-val = 0.371
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹
## intrcpt 0.454 0.182 2.496 47.01 0.016 0.088
## nmda_cumulative_exposure -0.002 0.001 -1.404 1.15 0.371 -0.012
## ci.ub¹
## intrcpt 0.819 *
## nmda_cumulative_exposure 0.009
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
Meta-regression of cumulative exposure versus effect size. The regression coefficient indicates whether increasing cumulative exposure is associated with changes in effect size, suggesting a potential dose–response relationship.
Log-transformed cumulative exposure
##
## Multivariate Meta-Analysis Model (k = 166; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.219 1.104 49 no study_id
## sigma^2.2 0.156 0.395 115 no study_id/exp_id
##
## Test for Residual Heterogeneity:
## QE(df = 164) = 876.670, p-val < .001
##
## Number of estimates: 166
## Number of clusters: 49
## Estimates per cluster: 0-12 (mean: 3.25, median: 2)
##
## Test of Moderators (coefficient 2):¹
## F(df1 = 1, df2 = 5.87) = 2.604, p-val = 0.159
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹
## intrcpt 0.334 0.184 1.819 46.45 0.075 -0.035
## log_nmda_cumulative_exposure 0.412 0.255 1.614 5.87 0.159 -0.216
## ci.ub¹
## intrcpt 0.704 .
## log_nmda_cumulative_exposure 1.040
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t/F-tests and confidence intervals, df: Satterthwaite approx)
Meta-regression of log-transformed cumulative exposure. The log-transformed model evaluates potential non-linear exposure–effect relationships and the robustness of the association.
Sensitivity analyses
Rho sensitivity
## rho estimate ci
## 1 0.0 0.4963016 [0.142, 0.851]
## 2 0.3 0.4478885 [0.103, 0.792]
## 3 0.5 0.4000693 [0.062, 0.738]
## 4 0.8 0.2493791 [-0.094, 0.593]
Sensitivity of the overall effect to within-study correlation (rho). This analysis evaluates the robustness of the pooled effect size to assumptions about the correlation between multiple effect sizes within the same experiment. Each row reports the overall effect estimate (Hedges’ g) and 95% confidence interval obtained under a different assumed value of rho. Stability of estimates across rho values indicates robustness to within-study dependency assumptions.
Leave-one-study-out
## left_out_study estimate ci_lb ci_ub
## 1 becker_2004 0.3975451 0.05078782 0.7443025
## 2 corbett_1993 0.4216986 0.08043758 0.7629596
## 3 corbett_1995 0.3939563 0.04731135 0.7406013
## 4 dunn_1989 0.3992372 0.05440548 0.7440690
## 5 gacsalyi_2013 0.3863922 0.04364818 0.7291363
## 6 georgiadou_2013 0.4632651 0.14284978 0.7836804
## 7 gururajan_2010 0.3997394 0.05275272 0.7467261
## 8 gururajan_2011 0.3873823 0.04187492 0.7328897
## 9 haller_2005 0.4079994 0.06412950 0.7518693
## 10 hereta_2019 0.4222760 0.07907403 0.7654780
## 11 kaminska_2015 0.4107951 0.06619306 0.7553972
## 12 koros_2007 0.3908981 0.04458268 0.7372136
## 13 kovanyi_2016 0.4062544 0.06156190 0.7509470
## 14 lafioniatis_2016 0.4347309 0.09860036 0.7708614
## 15 li_2018 0.3819516 0.03879085 0.7251123
## 16 maaswinkel_2013 0.3869800 0.04211392 0.7318461
## 17 maehara_2011 0.4212613 0.07870589 0.7638168
## 18 matsuoka_2005 0.3639464 0.02763662 0.7002561
## 19 matsuoka_2008 0.3638407 0.02759701 0.7000845
## 20 morimoto_2002 0.4017572 0.05548640 0.7480279
## 21 neill_2016 0.4095787 0.06561074 0.7535467
## 22 peters_2017 0.4139121 0.07078581 0.7570384
## 23 podhorna_2003 0.3634735 0.02799127 0.6989557
## 24 pouzet_2002 0.3753292 0.03510382 0.7155546
## 25 pouzet_2002b 0.3810141 0.03731244 0.7247159
## 26 rung_2005 0.4039851 0.05926397 0.7487061
## 27 rung_2005b 0.3926086 0.04638087 0.7388363
## 28 salunke_2013 0.4069477 0.06228971 0.7516057
## 29 sams-dodd_1995 0.4194214 0.07683253 0.7620103
## 30 sams-dodd_1996 0.3793567 0.03171470 0.7269987
## 31 sams-dodd_1997 0.3678853 0.02795536 0.7078153
## 32 sams-dodd_1998 0.3491921 0.02346068 0.6749235
## 33 sams-dodd_1998b 0.3760975 0.03478288 0.7174120
## 34 sams-dodd_1998c 0.3756845 0.03305872 0.7183102
## 35 sams-dodd_1998d 0.3756334 0.03367703 0.7175898
## 36 sams-dodd_2004 0.4073744 0.06303531 0.7517134
## 37 satow_2009 0.4273704 0.08626883 0.7684719
## 38 savage_2011 0.4688266 0.15195277 0.7857004
## 39 savolainen_2018 0.4094442 0.06481252 0.7540760
## 40 silvestre_1997 0.4076892 0.06402625 0.7513522
## 41 sukhotina_1998 0.4068999 0.06206553 0.7517342
## 42 tanaka_2003 0.3572838 0.02648715 0.6880805
## 43 tanaka_2019 0.3922819 0.04716314 0.7374006
## 44 tarland_2017 0.4128575 0.06959514 0.7561199
## 45 tarland_2018 0.4137049 0.07060884 0.7568009
## 46 trevlopoulou_2015 0.4401257 0.10604559 0.7742059
## 47 vijeepallam_2016 0.3836242 0.04036572 0.7268826
## 48 wass_2009 0.4054842 0.06157279 0.7493957
## 49 yeap_2020 0.3834551 0.03958427 0.7273260
## 50 zou_2008 0.4151293 0.07181974 0.7584388
## 51 zoupa_2019 0.4372366 0.10180206 0.7726712Leave-one-study-out analysis. Each row reports the pooled effect size (Hedges’ g) and 95% confidence interval obtained after excluding one study at a time from the meta-analysis. This analysis evaluates the influence of individual studies on the overall estimate; substantial changes after removal of a study would indicate disproportionate influence.
Excluding high risk of bias
##
## Multivariate Meta-Analysis Model (k = 96; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 1.030 1.015 26 no study_id
## sigma^2.2 0.317 0.563 66 no study_id/exp_id
##
## Test for Heterogeneity:
## Q(df = 95) = 579.671, p-val < .001
##
## Number of estimates: 96
## Number of clusters: 26
## Estimates per cluster: 0-12 (mean: 1.88, median: 1)
##
## Model Results:
##
## estimate se¹ tval¹ df¹ pval¹ ci.lb¹ ci.ub¹
## 0.778 0.231 3.365 24.36 0.003 0.301 1.255 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
## approx t-test and confidence interval, df: Satterthwaite approx)
Overall effect excluding high risk-of-bias studies. This sensitivity analysis re-estimates the overall meta-analytic effect after excluding studies classified as having high risk of bias. The purpose of this analysis is to assess whether the pooled effect estimate is robust to the exclusion of potentially biased evidence.
Annex: Individual effect sizes included in the meta-analysis
Calculated effect sizes
##
## study effect_id nmda_antagonist hedges_g ci_lb ci_ub
## 1 Gururajan 2011 35 MK-801 2.019 0.992 3.046
## 2 Gururajan 2011 39 MK-801 2.040 0.959 3.121
## 3 Gururajan 2011 43 MK-801 1.940 0.877 3.003
## 4 Gururajan 2011 36 MK-801 0.462 -0.385 1.308
## 5 Gururajan 2011 40 MK-801 0.467 -0.421 1.355
## 6 Gururajan 2011 44 MK-801 0.468 -0.421 1.356
## 7 Li 2018 53 MK-801 1.330 0.377 2.284
## 8 Podhorna 2003 109 Phencyclidine 1.935 0.956 2.914
## 9 Podhorna 2003 110 Phencyclidine 3.720 2.391 5.050
## 10 Podhorna 2003 111 Phencyclidine 4.408 2.920 5.896
## 11 Salunke 2013 119 MK-801 -0.419 -2.036 1.199
## 12 Salunke 2013 125 MK-801 0.181 -1.422 1.785
## 13 Salunke 2013 120 MK-801 -0.246 -1.853 1.360
## 14 Salunke 2013 121 MK-801 0.278 -1.330 1.886
## 15 Sams-Dodd 1997 128 Phencyclidine 3.133 1.939 4.327
## 16 Sams-Dodd 1997 130 Phencyclidine 1.792 0.845 2.739
## 17 Sams-Dodd 1997 132 Phencyclidine 0.739 -0.088 1.566
## 18 Sams-Dodd 1997 134 Phencyclidine 2.140 1.136 3.143
## 19 Sams-Dodd 1997 136 Phencyclidine 1.794 0.847 2.742
## 20 Sams-Dodd 1997 138 Phencyclidine 2.203 1.189 3.218
## 21 Sams-Dodd 1997 140 Phencyclidine 2.044 1.057 3.032
## 22 Sams-Dodd 1997 142 Phencyclidine 1.134 0.272 1.996
## 23 Sams-Dodd 1997 144 Phencyclidine 1.316 0.434 2.199
## 24 Sams-Dodd 1997 146 Phencyclidine 1.782 0.836 2.727
## 25 Sams-Dodd 1998 148 Phencyclidine 5.102 3.452 6.752
## 26 Sams-Dodd 1998 150 Phencyclidine 2.640 1.545 3.734
## 27 Sams-Dodd 1998 152 Phencyclidine 2.740 1.626 3.855
## 28 Sams-Dodd 1998 154 Phencyclidine 1.878 0.917 2.838
## 29 Sams-Dodd 1998 b 159 Phencyclidine 2.930 1.600 4.260
## 30 Sams-Dodd 1998 b 160 Phencyclidine 4.287 2.609 5.965
## 31 Sams-Dodd 1998 b 161 Phencyclidine 7.032 4.556 9.507
## 32 Sams-Dodd 1998 b 162 Phencyclidine 1.670 0.597 2.743
## 33 Sams-Dodd 1998 c 164 Phencyclidine 1.097 0.239 1.956
## 34 Sams-Dodd 1998 c 166 Phencyclidine 1.607 0.687 2.527
## 35 Sams-Dodd 1998 c 168 Phencyclidine 1.974 0.998 2.950
## 36 Sams-Dodd 1998 c 170 Phencyclidine 1.265 0.388 2.141
## 37 Savolainen 2018 171 Phencyclidine -0.062 -0.803 0.679
## 38 Savolainen 2018 172 Phencyclidine -0.159 -0.901 0.583
## 39 Tanaka 2019 200 MK-801 0.731 -0.034 1.496
## 40 Tarland 2018 205 Phencyclidine -0.388 -1.445 0.670
## 41 Zoupa 2019 215 Ketamine -1.602 -2.729 -0.476
## 42 Gururajan 2010 248 MK-801 0.122 -0.572 0.816
## 43 Gururajan 2010 252 MK-801 -0.121 -0.837 0.595
## 44 Gururajan 2010 258 MK-801 -0.116 -0.833 0.600
## 45 Gururajan 2010 262 MK-801 1.829 1.004 2.654
## 46 Gururajan 2010 249 MK-801 -0.338 -1.036 0.359
## 47 Gururajan 2010 255 MK-801 0.035 -0.680 0.751
## 48 Gururajan 2010 259 MK-801 0.028 -0.688 0.744
## 49 Gururajan 2010 263 MK-801 1.050 0.311 1.789
## 50 Koros 2007 284 MK-801 0.948 -0.246 2.141
## 51 Koros 2007 285 MK-801 2.311 0.850 3.772
## 52 Koros 2007 286 MK-801 1.763 0.429 3.096
## 53 Koros 2007 287 MK-801 3.314 1.571 5.057
## 54 Koros 2007 276 Phencyclidine 1.900 0.787 3.014
## 55 Koros 2007 277 Phencyclidine 1.051 0.065 2.037
## 56 Koros 2007 292 Ketamine 0.576 -0.579 1.731
## 57 Koros 2007 278 Phencyclidine 0.353 -0.578 1.284
## 58 Koros 2007 293 Ketamine -1.060 -2.269 0.148
## 59 Koros 2007 279 Phencyclidine 1.090 0.100 2.080
## 60 Koros 2007 294 Ketamine -1.980 -3.361 -0.599
## 61 Koros 2007 295 Ketamine -4.001 -5.961 -2.040
## 62 Kovanyi 2016 300 Phencyclidine 1.397 0.420 2.375
## 63 Kovanyi 2016 301 Phencyclidine -1.230 -2.185 -0.274
## 64 Pouzet 2002 323 Phencyclidine 1.941 0.568 3.313
## 65 Pouzet 2002 b 325 Phencyclidine 2.279 0.826 3.733
## 66 Pouzet 2002 b 327 Phencyclidine 0.549 -0.603 1.702
## 67 Savage 2011 348 Phencyclidine -3.577 -5.028 -2.126
## 68 Kaminska 2015 423 MK-801 0.318 -0.821 1.457
## 69 Kaminska 2015 426 MK-801 -0.651 -1.812 0.510
## 70 Maehara 2011 432 MK-801 -0.999 -2.009 0.011
## 71 Maehara 2011 434 MK-801 -0.204 -1.130 0.722
## 72 Sukhotina 1998 475 MK-801 -0.312 -1.194 0.570
## 73 Sukhotina 1998 476 MK-801 -0.178 -1.056 0.700
## 74 Sukhotina 1998 477 MK-801 0.531 -0.361 1.423
## 75 Trevlopoulou 2015 482 Ketamine -1.765 -2.920 -0.610
## 76 Zou 2008 520 MK-801 -0.403 -1.211 0.405
## 77 Dunn 1989 569 MK-801 0.132 -1.000 1.265
## 78 Dunn 1989 570 MK-801 0.653 -0.508 1.815
## 79 Gacsalyi 2013 573 Phencyclidine 1.246 -0.269 2.760
## 80 Haller 2005 579 Phencyclidine -1.075 -2.401 0.251
## 81 Haller 2005 580 Phencyclidine 0.753 -0.530 2.036
## 82 Lafioniatis 2016 593 Ketamine -1.602 -2.902 -0.301
## 83 Maaswinkel 2013 607 MK-801 0.742 0.101 1.382
## 84 Maaswinkel 2013 608 MK-801 1.011 0.352 1.669
## 85 Maaswinkel 2013 609 MK-801 2.800 1.916 3.683
## 86 Matsuoka 2008 611 MK-801 2.298 1.569 3.027
## 87 Neill 2016 620 Phencyclidine -0.161 -1.142 0.821
## 88 Peters 2017 624 Phencyclidine -0.391 -1.415 0.633
## 89 Sams-Dodd 1996 629 Phencyclidine -1.231 -2.103 -0.358
## 90 Sams-Dodd 1996 635 MK-801 0.527 -0.287 1.341
## 91 Sams-Dodd 1996 636 MK-801 -0.452 -1.263 0.358
## 92 Sams-Dodd 1996 637 MK-801 1.275 0.398 2.153
## 93 Sams-Dodd 1996 638 MK-801 3.868 2.512 5.223
## 94 Sams-Dodd 1996 639 MK-801 4.030 2.637 5.423
## 95 Sams-Dodd 1996 641 Phencyclidine 1.739 0.800 2.678
## 96 Sams-Dodd 1996 645 Phencyclidine 0.914 0.073 1.755
## 97 Sams-Dodd 1996 643 Phencyclidine 1.834 0.880 2.788
## 98 Sams-Dodd 1996 647 Phencyclidine 1.916 0.949 2.882
## 99 Sams-Dodd 1998 d 648 Phencyclidine 1.837 0.883 2.791
## 100 Sams-Dodd 1998 d 650 Phencyclidine 1.517 0.609 2.425
## 101 Sams-Dodd 1998 d 652 Phencyclidine 1.824 0.478 3.171
## 102 Sams-Dodd 1998 d 654 Phencyclidine 1.925 0.957 2.893
## 103 Sams-Dodd 1998 d 656 Phencyclidine 1.123 0.262 1.984
## 104 Sams-Dodd 1998 d 658 Phencyclidine 1.676 0.746 2.606
## 105 Sams-Dodd 1998 d 660 Phencyclidine 1.119 0.259 1.980
## 106 Sams-Dodd 1998 d 662 Phencyclidine 1.182 -0.045 2.408
## 107 Vijeepallam 2016 690 Ketamine 1.271 0.196 2.345
## 108 Becker 2004 712 Ketamine 0.761 -0.254 1.776
## 109 Becker 2004 715 Ketamine 0.785 -0.174 1.743
## 110 Becker 2004 718 Ketamine 0.679 -0.277 1.634
## 111 Becker 2004 721 Ketamine 1.041 0.051 2.031
## 112 Becker 2004 724 Ketamine 1.172 0.167 2.177
## 113 Becker 2004 727 Ketamine 0.330 -0.628 1.289
## 114 Becker 2004 700 Ketamine 0.432 -0.414 1.277
## 115 Becker 2004 703 Ketamine 0.526 -0.414 1.466
## 116 Becker 2004 706 Ketamine -0.348 -1.211 0.515
## 117 Becker 2004 709 Ketamine 0.546 -0.395 1.487
## 118 Corbett 1993 741 MK-801 -0.948 -2.142 0.245
## 119 Corbett 1993 742 MK-801 -0.631 -1.791 0.528
## 120 Georgiadou 2013 749 Ketamine -3.430 -4.970 -1.889
## 121 Rung 2005 819 MK-801 -0.598 -1.755 0.558
## 122 Rung 2005 820 MK-801 -0.517 -1.668 0.633
## 123 Rung 2005 821 MK-801 1.103 -0.112 2.317
## 124 Rung 2005 822 MK-801 0.958 -0.237 2.153
## 125 Satow 2009 824 MK-801 -1.506 -2.788 -0.224
## 126 Satow 2009 826 MK-801 -0.391 -1.113 0.332
## 127 Satow 2009 828 MK-801 -0.713 -1.880 0.454
## 128 Tarland 2017 835 Phencyclidine -0.344 -1.399 0.712
## 129 Corbett 1995 879 Phencyclidine -0.490 -1.638 0.659
## 130 Corbett 1995 880 Phencyclidine 0.845 -0.336 2.026
## 131 Corbett 1995 883 Phencyclidine 1.095 -0.119 2.308
## 132 Corbett 1995 885 Phencyclidine 0.743 -0.427 1.913
## 133 Corbett 1995 887 Phencyclidine 1.343 0.090 2.595
## 134 Corbett 1995 889 Phencyclidine 0.102 -1.030 1.235
## 135 Corbett 1995 891 Phencyclidine -0.105 -1.237 1.028
## 136 Corbett 1995 893 Phencyclidine 1.381 0.122 2.640
## 137 Corbett 1995 895 Phencyclidine 0.487 -0.661 1.636
## 138 Corbett 1995 881 Phencyclidine 2.092 0.684 3.499
## 139 Hereta 2019 970 MK-801 -0.372 -1.514 0.769
## 140 Hereta 2019 973 MK-801 -0.512 -1.662 0.638
## 141 Hereta 2019 976 MK-801 -0.184 -1.318 0.950
## 142 Hereta 2019 979 MK-801 -0.393 -1.535 0.750
## 143 Hereta 2019 981 MK-801 -0.960 -2.155 0.235
## 144 Matsuoka 2005 1007 MK-801 2.291 1.563 3.019
## 145 Morimoto 2002 1012 MK-801 -0.870 -2.167 0.427
## 146 Morimoto 2002 1014 MK-801 0.753 -0.530 2.035
## 147 Morimoto 2002 1017 MK-801 -0.029 -1.269 1.210
## 148 Morimoto 2002 1019 MK-801 1.172 -0.170 2.513
## 149 Rung 2005 b 1058 MK-801 1.076 0.087 2.064
## 150 Rung 2005 b 1060 MK-801 0.730 -0.438 1.899
## 151 Rung 2005 b 1062 MK-801 0.600 -0.668 1.867
## 152 Rung 2005 b 1064 MK-801 0.478 -0.301 1.258
## 153 Sams-Dodd 1995 1083 Phencyclidine -0.038 -0.962 0.886
## 154 Sams-Dodd 1995 1084 Phencyclidine -0.335 -1.266 0.595
## 155 Sams-Dodd 1995 1085 Phencyclidine 0.080 -0.844 1.005
## 156 Sams-Dodd 1995 1086 Phencyclidine 0.550 -0.391 1.492
## 157 Sams-Dodd 1995 1087 Phencyclidine 1.594 0.533 2.655
## 158 Sams-Dodd 1995 1088 Phencyclidine 2.439 1.219 3.659
## 159 Sams-Dodd 1995 1089 Phencyclidine 3.206 1.810 4.603
## 160 Sams-Dodd 1995 1090 Phencyclidine 3.876 2.308 5.443
## 161 Sams-Dodd 1995 1091 Phencyclidine 0.361 -0.571 1.292
## 162 Sams-Dodd 2004 1098 MK-801 2.820 1.222 4.418
## 163 Sams-Dodd 2004 1096 MK-801 -0.223 -1.358 0.912
## 164 Sams-Dodd 2004 1099 MK-801 -0.641 -1.801 0.520
## 165 Sams-Dodd 2004 1097 MK-801 1.118 -0.099 2.335
## 166 Silvestre 1997 1102 Ketamine -0.101 -1.341 1.140
## 167 Tanaka 2003 1107 MK-801 4.709 3.155 6.263
## 168 Tanaka 2003 1106 Phencyclidine 2.596 1.510 3.682
## 169 Wass 2009 1122 Phencyclidine 0.024 -1.215 1.264
## 170 Yeap 2020 1132 MK-801 1.198 0.425 1.972Individual effect sizes included in the meta-analysis. This table lists all calculated Hedges’ g values and corresponding confidence intervals used in the analyses.
Session info
## R version 4.3.1 (2023-06-16 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 11 x64 (build 26100)
##
## Matrix products: default
##
##
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8 LC_CTYPE=Portuguese_Brazil.utf8
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C
## [5] LC_TIME=Portuguese_Brazil.utf8
##
## time zone: America/Sao_Paulo
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] RColorBrewer_1.1-3 scales_1.4.0 stringr_1.5.1
## [4] forcats_1.0.1 ggalluvial_0.12.5 tidyr_1.3.1
## [7] ggplot2_4.0.0 orchaRd_2.1.3 clubSandwich_0.6.1
## [10] metafor_4.8-0 numDeriv_2016.8-1.1 metadat_1.2-0
## [13] Matrix_1.6-5 dplyr_1.1.4 readxl_1.4.5
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.6 beeswarm_0.4.0 xfun_0.52 bslib_0.9.0
## [5] lattice_0.22-6 mathjaxr_1.6-0 vctrs_0.6.5 tools_4.3.1
## [9] generics_0.1.4 sandwich_3.1-1 tibble_3.2.1 pkgconfig_2.0.3
## [13] S7_0.2.0 lifecycle_1.0.4 compiler_4.3.1 farver_2.1.2
## [17] textshaping_1.0.0 prettydoc_0.4.1 codetools_0.2-20 vipor_0.4.7
## [21] htmltools_0.5.8.1 sass_0.4.9 yaml_2.3.10 pillar_1.11.1
## [25] jquerylib_0.1.4 MASS_7.3-60.0.1 cachem_1.1.0 multcomp_1.4-28
## [29] nlme_3.1-164 tidyselect_1.2.1 digest_0.6.35 mvtnorm_1.3-3
## [33] stringi_1.8.7 purrr_1.0.2 labeling_0.4.3 splines_4.3.1
## [37] latex2exp_0.9.6 fastmap_1.2.0 grid_4.3.1 cli_3.6.2
## [41] magrittr_2.0.3 survival_3.5-8 TH.data_1.1-4 withr_3.0.2
## [45] ggbeeswarm_0.7.2 estimability_1.5.1 rmarkdown_2.30 emmeans_1.11.2-8
## [49] cellranger_1.1.0 ragg_1.3.3 zoo_1.8-13 evaluate_1.0.5
## [53] knitr_1.50 rlang_1.1.5 xtable_1.8-4 glue_1.8.0
## [57] rstudioapi_0.17.1 jsonlite_2.0.0 R6_2.6.1 systemfonts_1.2.2